We propose a full reference stereo video quality assessment
algorithm for assessing the perceptual quality of natural stereo
videos. We exploit the separable representation of motion
and binocular disparity in the visual cortex and develop a
four stage algorithm to measure the quality of a stereoscopic
video called FLOSIM3D. First, we compute the temporal features
by utilizing an existing 2D VQA metric which measures
the temporal annoyance based on patch level statistics such
as mean, variance and minimum eigen value and pools them
with a frame categorization based non-linear pooling strategy.
Second, a structure based 2D Image Quality Assessment
(IQA) metric is used to compute the spatial quality of
the frames. Next, the loss in depth cues is measured using
a structure based metric. Finally, the features for each of the
stereo views are pooled to obtain the final stereo video quality
score. We demonstrate the state-of-the-art performance of the
proposed metric on IRCCYN dataset involving H.264, JP2K
compression artifacts.